Conference

Abstract

The emergence of large language models (LLMs) has revolutionized the AI field, offering unprecedented capabilities in reasoning, generalization, and zero-shot learning. These strengths open new frontiers in wireless communications, where increasing complexity and dynamism demand intelligent and adaptive solutions. This talk explores the role of LLMs in transforming wireless systems across three key directions: adapting pretrained LLMs for core communication tasks, developing wireless-specific foundation models to balance versatility and efficiency, and enabling agentic LLMs with autonomous reasoning and coordination capabilities. We highlight recent advances, practical case studies, and the unique benefits of LLM-based approaches over traditional methods. Finally, we outline open challenges and research opportunities.

Bios

Geoffrey Ye Li, FREng (Fellow of Royal Academic of Engineering) and Fellow of IEEE, is a Chair Professor at Imperial College London, UK. Before joining Imperial in 2020, he was a Professor at Georgia Institute of Technology, USA, for 20 years and a Principal Technical Staff Member with AT&T Labs – Research (previous Bell Labs), USA, for five years. He is the first to introduce deep learning to communications in 2016, which has become a popular research area now. He made fundamental contributions to orthogonal frequency division multiplexing (OFDM) for wireless communications, which made him win 2024 IEEE Eric E. Sumner Technical-Field Award. He also won several awards from IEEE Signal Processing, Vehicular Technology, and Communications Societies, including 2019 IEEE ComSoc Edwin Howard Armstrong Achievement Award.